Search results for: radiographic abnormalities

Authors: Delsy Salinas, Andreia Garcês, Augusto Silva, Paula Brilhante Simões

Abstract:

Urinary tract infection (UTI) is a common disease affecting dogs and cats in both community and hospital environment. Bacteria is the most frequent agent isolated, fewer than 1% of infections are due to parasitic, fungal, or viral agents. Common symptoms and laboratory abnormalities includeabdominal pain, pyrexia, renomegaly, and neutrophilia with left shift. A rapid and precise identification of the bacterial agent is still a challenge in veterinarian laboratories. Therefore, this cross-sectional study aims to describe bacterial colony patterns of urine samples by using chromID™ CPS® EliteAgar (BioMérieux, France) from canine and feline specimens submitted to a veterinary laboratory in Portugal (INNO Veterinary Laboratory, Braga)from January to March2022. All urine samples were cultivated in CPS Elite Agar with calibrated 1 µL inoculating loop and incubated at 37ºC for 18-24h. Color,size, and shape (regular or irregular outline)were recorded for all samples. All colonies were classified as Gram-negative or Gram-positive bacteriausing Gram stain (PREVI® Color BioMérieux, France) and determined if they were pure colonies. Identification of bacteria species was performed using GP and GN cards inVitek 2® Compact(BioMérieux, France). A total of 256/1003 submitted urine samples presented bacterial growth, from which 172 isolates were included in this study. The sample’s population included 111 dogs (n=45 males and n=66 females) and 61 cats (n=35 males and n=26 females). The most frequent isolated bacteria wasEscherichia coli (44,7%), followed by Proteus mirabilis (13,4%). All Escherichia coli isolates presented red to burgundy colonies, a colony diameter between 2 to 6 mm, and regular or irregular outlines. Similarly, 100% of Proteus mirabilis isolates were dark yellow colonies with a diffuse pigment and the same size and shape as Escherichia coli. White and pink pale colonies where Staphylococcus species exclusively and S. pseudintermedius was the most frequent (8,2 %). Cian to blue colonies were mostly Enterococcusspp. (8,2%) and Streptococcus spp. (4,6%). Beige to brown colonies were Pseudomonas aeruginosa (2,9%) and Citrobacter spp. (1,2%).Klebsiella spp.,Serratia spp. and Enterobacter spp were green colonies. All Gram-positive isolates were 1 to 2 mm diameter long and had a regular outline, meanwhile, Gram-negative rods presented variable patterns. This results showed that theprevalence of E coli and P. mirabilis as uropathogenic agents follows the same trends in Europe as previously described in other studies. Both agents presented a particular color pattern in CPS Elite Agar to identify them without needing complementary tests. No other bacteria genus could be correlated strongly to a specific color pattern, and similar results have been observed instudies using human’s samples. Chromogenic media shows a great advantage for common urine bacteria isolation than traditional COS, McConkey, and CLEDAgar mediums in a routine context, especially when mixed fermentative Gram-negative agents grow simultaneously. In addition, CPS Elite Agar is versatile for Artificial Intelligent Reading Plates Systems. Routine veterinarian laboratories could use CPS Elite Agar for a rapid screening for bacteria identification,mainlyE coli and P.mirabilis, saving 6h to 10h of automatized identification.

Keywords: cats, CPS elite agar, dogs, urine pathogens

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Authors: Kuladip Jana

Abstract:

Benzo(a)pyrene [B(a)P] is an environmental toxicant present mostly in cigarette smoke and car exhaust, is an aryl hydrocarbon receptor (AhR) ligand that exerts its toxic effects on both male and female reproductive systems. In this study, the effect of B(a)P at different doses (0.1, 0.25, 0.5, 1 and 5 mg /kg body weight) was studied on male reproductive system of rat. A significant decrease in cauda epididymal sperm count and motility along with the presence of sperm head abnormalities and altered epididymal and testicular histology were documented following B(a)P treatment. B(a)P treatment resulted apoptotic sperm cells as observed by TUNEL and Annexin V-PI assay with increased ROS, altered sperm mitochondrial membrane potential (ΔΨm) with a simultaneous decrease in the activity of antioxidant enzymes and GSH status. TUNEL positive apoptotic cells also observed in testis as well as isolated germ and Leydig cells following B(a)P exposure. Western Blot analysis revealed the activation of p38MAPK, cytosolic translocation of cytochrome-c, up-regulation of Bax and inducible nitric oxide synthase (iNOS) with cleavage of PARP and down-regulation of BCl2 in testis upon B(a)P treatment. The protein and mRNA levels of testicular key steroidogenesis regulatory proteins like StAR, cytochrome P450 IIA1 (CYPIIA1), 3β HSD, 17β HSD showed a significant decrease in a dose dependent manner while an increase in the expression of cytochrome P450 1A1 (CYP1A1), Aryl hydrocarbon Receptor (AhR), active caspase- 9 and caspase- 3 following B(a)P exposure. We conclude that exposure of benzo(a)pyrene caused testicular gamatogenic and steroidogenic disorders by induction of oxidative stress, inhibition of StAR and other steroidogenic enzymes along with activation of p38MAPK and initiated caspase-3 mediated germ and Leydig cell apoptosis.The possible protective role of naturally occurring phytochemicals against B(a)P induced testicular toxicity needs immediate consideration. Curcumin and resveratrol separately were found to protect against B(a)P induced germ cell apoptosis, and their combinatorial effect was more significant. Our present study in isolated testicular germ cell population from adult male Wistar rats, highlighted their synergistic protective effect against B(a)P induced germ cell apoptosis. Curcumin-resveratrol co-treatment decreased the expression of pro-apoptotic proteins like cleaved caspase 3,8,9, cleaved PARP, Apaf1, FasL, tBid. Curcumin-resveratrol co-treatment decreased Bax/Bcl2 ratio, mitochondria to cytosolic translocation of cytochrome c and activated the survival protein Akt. Curcumin-resveratrol decreased the expression of p53 dependent apoptotic genes like Fas, FasL, Bax, Bcl2, Apaf1.Curcumin-resveratrol co-treatment thus prevented B(a)P induced germ cell apoptosis. B(a)P induced testicular ROS generation and oxidative stress were significantly ameliorated with curcumin and resveratrol. Curcumin-resveratrol co-treatment prevented B(a)P induced nuclear translocation of AhR and CYP1A1 production. The combinatorial treatment significantly inhibited B(a)P induced ERK 1/2, p38 MAPK and JNK 1/2 activation. B(a)P treatment increased the expression of p53 and its phosphorylation (p53 ser 15). Curcumin-resveratrol co-treatment significantly decreased p53 level and its phosphorylation (p53 ser 15). The study concludes that curcumin-resveratrol synergistically modulated MAPKs and p53, prevented oxidative stress, regulated the expression of pro and anti-apoptotic proteins as well as the proteins involved in B(a)P metabolism thus protected germ cells from B(a)P induced apoptosis.

Keywords: benzo(a)pyrene, germ cell, apoptosis, oxidative stress, resveratrol, curcumin

Procedia PDF Downloads 241

Authors: Kuladip Jana, Bhaswati Banerjee, Parimal C. Sen

Abstract:

Benzo(a)pyrene [B(a)P] is an environmental toxicant present mostly in cigarette smoke and car exhaust, is an aryl hydrocarbon receptor (AhR) ligand that exerts its toxic effects on both male and female reproductive systems along with carcinogenesis in skin, prostate, ovary, lung and mammary glands. Our study was focused on elucidating the molecular mechanism of B(a)P induced male reproductive toxicity and its prevention with phytochemical like resveratrol. In this study, the effect of B(a)P at different doses (0.1, 0.25, 0.5, 1 and 5 mg /kg body weight) was studied on male reproductive system of Wistar rat. A significant decrease in cauda epididymal sperm count and motility along with the presence of sperm head abnormalities and altered epididymal and testicular histology were documented following B(a)P treatment. B(a)P treatment resulted apoptotic sperm cells as observed by TUNEL and Annexin V-PI assay with increased Reactive Oxygen Species (ROS), altered sperm mitochondrial membrane potential (ΔΨm) with a simultaneous decrease in the activity of antioxidant enzymes and GSH status. TUNEL positive apoptotic cells also observed in testis as well as isolated germ and Leydig cells following B(a)P exposure. Western Blot analysis revealed the activation of p38 mitogen activated protein kinase (p38MAPK), cytosolic translocation of cytochrome-c, upregulation of Bax and inducible nitric oxide synthase (iNOS) with cleavage of poly ADP ribose polymerase (PARP) and down regulation of BCl2 in testis upon B(a)P treatment. The protein and mRNA levels of testicular key steroidogenesis regulatory proteins like steroidogenic acute regulatory protein (StAR), cytochrome P450 IIA1 (CYPIIA1), 3β hydroxy steroid dehydrogenase (3β HSD), 17β hydroxy steroid dehydrogenase (17β HSD) showed a significant decrease in a dose dependent manner while an increase in the expression of cytochrome P450 1A1 (CYP1A1), Aryl hydrocarbon Receptor (AhR), active caspase- 9 and caspase- 3 following B(a)P exposure. We conclude that exposure of benzo(a)pyrene caused testicular gamatogenic and steroidogenic disorders by induction of oxidative stress, inhibition of StAR and other steroidogenic enzymes along with activation of p38MAPK and initiated caspase-3 mediated germ and Leydig cell apoptosis. Next we investigated the role of resveratrol on B(a)P induced male reproductive toxicity. Our study highlighted that resveratrol co-treatment with B(a)P maintained testicular redox potential, increased serum testosterone level and prevented steroidogenic dysfunction with enhanced expression of major testicular steroidogenic proteins (CYPIIA1, StAR, 3β HSD,17β HSD) relative to treatment with B(a)P only. Resveratrol suppressed B(a)P-induced testicular activation of p38 MAPK, ATF2, iNOS and ROS production; cytosolic translocation of Cytochome c and Caspase 3 activation thereby prevented oxidative stress of testis and inhibited apoptosis. Resveratrol co-treatment also decreased B(a)P-induced AhR protein level, its nuclear translocation and subsequent CYP1A1 promoter activation, thereby decreased protein and mRNA levels of testicular cytochrome P4501A1 (CYP1A1) and prevented BPDE-DNA adduct formation. Our findings cumulatively suggest that resveratrol prevents activation of B(a)P by modulating the transcriptional regulation of CYP1A1 and acting as an antioxidant thus prevents B(a)P-induced oxidative stress and testicular apoptosis.

Keywords: benzo(a)pyrene, resveratrol, testis, apoptosis, cytochrome P450 1A1 (CYP1A1), aryl hydrocarbon receptor (AhR), p38 MAPK/ATF2/iNOS

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Authors: Pei Yi Lin

Abstract:

Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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